3 Surface ReconstructionAfter scanning an object into a point cloud, we want to get a mesh from those points.Method should be able to infer the topology of the unknown surface, accurately fit the noisy data, and fill holes reasonably.Poisson Surface Reconstruction is one of the approaches to obtain smooth and watertight surface.3

4 Practical DifficultiesThe point samples may not be uniformly distributed over the model surface.The positions and normals are generally noisy due to sampling inaccuracy and scan misregistration.And, accessibility constraints during scanning may leave some surface regions devoid of data.4

5 Poisson Reconstruction - ApproachIt computes a 3D indicator function X(defined as 1 at points inside the model, and 0 at points outside).The gradient of the indicator function is non- zero only at points near the surface,At such points, it is taken(proven) to be equal to the inward surface normal.5

6 Approach (contd.)Thus, the oriented point samples can be viewed as samples of the gradient of the model’s indicator functionThe problem reduces to finding X whose gradient best approximates a vector field V defined by the input points.∇X = V6

7 Approach (contd.)If we apply the divergence operator, this problem transforms into a standard Poisson problem: compute the scalar function X whose Laplacian (divergence of gradient) equals the divergence of the vector field V,ΔX ≡ ∇·∇X = ∇·VThe implicit function X is represented using an adaptive octree rather than a regular 3D grid.7

11 We have used Meshlab for experimentation. EvaluationWe have used Meshlab for experimentation.The generated mesh is affected by-Octree Depth: tree-depth that is used for the reconstruction.SamplesPerNode: specifies the maximum number of sample points that should fall within an octree node. For noise-free data: [1.0, 5.0], noisy data: [15.0, 20.0]11